How is AI transforming the future of the Healthcare industry?

Over the last 10 years, we have come to see robots perform and execute jobs that were once exclusive to humans – be it, manufacturing cars or filling warehouse orders.

As of today, we are no strangers to the fact that there are multiple industries that AI/ML have significantly impacted over the last couple years. However, the integration of Artificial Intelligence in Healthcare with a chatbot as your doctor is set to witness a significant paradigm shift.

We are already seeing image recognition algorithms assist in detecting diseases at an astounding rate and are only beginning to scratch the surface. Chatbots are slowly being adopted within healthcare, albeit being in their nascent stage. Grand View Research stipulates that the global chatbot market is estimated to touch at least $1.23 billion by 2025 which reflects a compounded annual growth rate (CAGR) of 24.3%.

Interestingly, one the first chatbots to be developed was ELIZA who happened to be a psychotherapist. Developed back in 1966, she was a computer program that simulated an actual therapy conversation to the extent that people actually believed that it was a human at the other end.

Here’s a snippet of the conversation with ELIZA –

The doctor-patient relationship has not changed over the years. As a patient, if you feel something is off, you go to the clinic and talk about the problem(s) you are facing. The doctor checks your vitals, scrutinizes a bit, offer a diagnosis and prescribes the relevant medication.

How does a conversational AI/chatbot come into the picture?

There are a myriad of health related queries and questions that honestly do not need the attention and time of a physician. There are times where the doctors are busy, and patients often take an appointment for an illness that would have passed with little rest, or in some cases where patients tend to fail in following up or following thorough the treatments once they leave the clinic. No matter how redundant, some questions can’t be left unanswered as well as they may result in concerned people feeling nervous and clueless.

Imagine parents with a new born baby. They have absolutely no experience. They will hound doctors with questions on their child’s well being. Whether it is the baby’s temperature, sleeping routine, vaccinations etc. Multiply this with 10 new parents asking the same set of questions to one doctor day after day. These are all relevant and important questions, but they do not need a response from a doctor. So what is the solution here? A health chatbot which is constantly supported and gradually taught by doctors.

An intelligent chatbot can guide the concerned parents or patients by understanding and assessing the symptoms that the patient is experiencing and identify the care that they need. With the help of a medical chatbot, patients can receive immediate assistance at the touch of their fingertips.

Chatbots can also engage patients and improve patient experience — without the need for a customer support team or a physician on the other end.

Additionally, they can also assist with setting up an appointment with the doctor at the right time based on the doctor’s schedule and hours.

Here’s how a conversation with a chatbot may go like —

Patient: Hello

Chatbot: Hey Jeff! What can I do for you today?

Patient: I’m running a temperature and getting the chills.

Chatbot: I’m sorry to hear that. The data from your smart band shows a temperature of 101 F with a regular pulse. How long have you been getting the chills?

Patient: Since last night.

Chatbot: I recommend you see your GP Dr. Susan. I’ll go ahead and schedule an appointment.

Chatbot: Hi Sam! How are you feeling today?

Patient: I have been feeling dizzy for the last hour.

Chatbot: Oh! Are you running a temperature?

Patient: Yes, 39*.

Chatbot: I see. You might be running a fever. The doctor is available after 6 PM today. Would you like me to book an appointment for you?

Patient: Yes, please!

Chatbot: Done! I have fixed your appointment.

As of now, use cases for healthcare chatbots include:

Scheduling doctor appointments based on complexity of a patient’s symptoms
Monitoring a patient’s health status and notifying a nurse immediately if the parameters are out of control
Assisting homecare assistants by keeping them informed about their patients

The primary use case of a chatbot as your doctor is to free-up a doctor’s time by cutting down or eliminating unnecessary appointments. Given the sky-rocketing operational costs, healthcare organizations are always looking for ways to keep them down while simultaneously improving the patient experience.

Apart from saving time, these intelligent chatbots can also execute tasks related to billing, stock, and insurance claims management as well.

Natural language processing is used to assess and understand a patient’s queries and is closely followed by knowledge management when it comes to providing an answer. Deep learning assists the healthcare chatbot in improving the for each interaction while sentiment analysis identifies the user’s frustration and hands over the conversation to a human.

With time, deep learning will help the healthcare bot in ameliorating the responses for every single interaction and also generate context-based replies through Natural Language Generation.

This way, a chatbot would be a better fit when it comes to patient engagement as compared to a standalone mobile application.

The best part? This process will not be limited to just one bot. The entire fleet of chatbots deployed in that particular vertical/service will learn from the past mistakes and continuously improve. With bots processing information rapidly, through sentiment analysis, they will learn when to direct the patient to a physician’s attention or call for help themselves.

How do you go about implementing a healthcare bot?

Healthcare companies ideally need to formulate an effective strategy for implementing emerging technologies like chatbots and AI by first defining the bot’s scope of knowledge.

What is the one key thing all healthcare organizations aim for? An enhanced patient experience.

For an unparalleled patient experience, your healthcare chatbot must come across as natural and straightforward while being available round the clock, understand and empathize with the patient and ultimately engage them in conversation by providing personalized and intelligent recommendations.

Post that, you must also leverage cutting-edge technologies and machine learning for your chatbot to get smarter over time as it starts receiving more data through patient interactions. Lastly, healthcare organizations should have a repository of data that is inclusive of their FAQs, online forms, email and call center records which the bot can leverage to further personalize the conversations.

Should we expect a bot revolution in the Healthcare industry?

Chatbots and Artificial Intelligence today are already revolutionizing different industries, including banking, hospitality, and e-commerce to name a few.

Doubtless to say, the healthcare sector will definitely benefit from the cost effectiveness of bots with the customer care aspect being automated. The impersonal nature of a bot could act as a benefit in certain situations, where an actual doctor is not needed. Conversational AI in healthcare eases the access to the right care and the industry has favorable chances to serve their patients with personalized health tips.

We’re very close to the time where the bot would notify the user that it is time for their annual mammogram based on past medical records and schedule an appointment, or have the pathology assistant book a visit to your home for your quarterly sugar test.

The healthcare industry is right on verge of being bot-o-mated very soon.

Mitul Makadia is Founder of Maruti Techlabs and a true technophile. With his industry experience, he has rapidly developed Maruti Techlabs in specialized services like Chatbot Development, Artificial Intelligence, Natural Language Processing and Machine Learning.
Makadia has considerable expertise in Chatbot Development and NLP.

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